Robust balance shift control with posture optimization

Kavafoglu, Zumra; Kavafoglu, Ersan; Egges, Arjan

doi:10.1145/2822013.2822020

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Due to the density of the crowd, however, such collisions are likely to occur. We are currently investigating a method employing physics-based characters that follows our torso planning method [43]. Such a system would be able to respond to collisions in a physically correct way, and be used to plan lower-body motion.…”

Section: Discussionmentioning

confidence: 99%

Torso Crowds

Stüvel

Magnenat‐Thalmann

Thalmann

et al. 2017

IEEE Trans. Visual. Comput. Graphics

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We present a novel dense crowd simulation method. In real crowds of high density, people manoeuvring the crowd need to twist their torso to pass between others. Our proposed method does not use the traditional disc-shaped agent, but instead employs capsule-shaped agents, which enables us to plan such torso orientations. Contrary to other crowd simulation systems, which often focus on the movement of the entire crowd, our method distinguishes between active agents that try to manoeuvre through the crowd, and passive agents that have no incentive to move. We introduce the concept of a focus point to influence crowd agent orientation. Recorded data from real human crowds are used for validation, which shows that our proposed model produces equivalent paths for 85 percent of the validation set. Furthermore, we present a character animation technique that uses the results from our crowd model to generate torso-twisting and side-stepping characters.

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Section: Discussionmentioning

confidence: 99%

Torso Crowds

Stüvel

Magnenat‐Thalmann

Thalmann

et al. 2017

IEEE Trans. Visual. Comput. Graphics

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“…A balance shift controller, which is the previous version of our approach, has been presented at Motion In Games 2015. That work focuses on balance shifting behaviours during standing, which is also formed of a kinematic posture optimizer and a physics‐based control framework. In this work, we improved the optimization technique such that it enables control on the vertical movement of the character COM and eliminates the need for devising a separate knee bending strategy.…”

Section: Related Workmentioning

confidence: 99%

Robust standing control with posture optimization

Kavafoglu

Egges

2017

Computer Animation & Virtual

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Humans need to shift their center of mass during standing for several purposes such as preparing for the upcoming motion or increasing their stability. In this paper, we present a control strategy for robust center of mass shifting motions during standing. In our strategy, the desired posture can be defined with only a few high level features, such as the desired character center of mass position and the foot configurations. An online optimization process is designed for generating a kinematic lower body and pelvis posture that satisfies these high level features together with some criteria that guide a natural standing pose. Natural knee bending behaviours automatically arise as a result of this optimization process. Internal joint torques for tracking this optimized posture together with the given desired upper body pose are calculated by the physics‐based control framework. Moreover, a physics‐based arm control strategy that regulates the angular momentum of the character is devised in order to increase the robustness of the character under external disturbances. Several experiments are conducted to demonstrate the effectiveness of the proposed strategy. Because the strategy does not include any off‐line parameter optimization, equations of motion, or inverse dynamics, it is highly suitable for online applications.

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Robust balance shift control with posture optimization

Cited by 2 publications

References 33 publications

Torso Crowds

Torso Crowds

Robust standing control with posture optimization

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